EC ENGR 236C · EE 236COptimization Methods for Large-Scale Systems
Electrical and Computer Engineering · 4 units · Graduate courses (200-299)
First-order algorithms for convex optimization: subgradient method, conjugate gradient method, proximal gradient and accelerated proximal gradient methods, block coordinate descent. Decomposition of large-scale optimization problems. Augmented Lagrangian method and alternating direction method of multipliers. Monotone operators and operator-splitting algorithms. Second-order algorithms: inexact Newton methods, interior-point algorithms for conic optimization.
Letter grading.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
Requisites
Official UCLA wording
Requisite: course 236B.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
EC ENGR 236C
- EC ENGR 236BConvex Optimization
- EC ENGR 236ALinear Programming
1 direct requisite. Showing 3 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.